Homology modeling and virtual screening approaches to identify potent inhibitors of VEB-1 β-lactamase

Homology Modeling, de Novo Design of Ligands, and Molecular Docking Identify Potential Inhibitors of Leishmania donovani 24-Sterol Methyltransferase

The therapeutic challenges pertaining to leishmaniasis due to reported chemoresistance and toxicity necessitate the need to explore novel pathways to identify plausible inhibitory molecules. Leishmania donovani 24-sterol methyltransferase (LdSMT) is vital for the synthesis of ergosterols, the main constituents of Leishmania cellular membranes. So far, mammals have not been shown to possess SMT or ergosterols, making the pathway a prime candidate for drug discovery. The structural model of LdSMT was elucidated using homology modeling to identify potential novel 24-SMT inhibitors via virtual screening, scaffold hopping, and de-novo fragment-based design. Altogether, six potential novel inhibitors were identified with binding energies ranging from −7.0 to −8.4 kcal/mol with e-LEA3D using 22,26-azasterol and S1–S4 obtained from scaffold hopping via the ChEMBL, DrugBank, PubChem, ChemSpider, and ZINC15 databases. These ligands showed comparable binding energy to 22,26-azasterol (−7.6 kcal/mol), the main inhibitor of LdSMT. Moreover, all the compounds had plausible ligand efficiency-dependent lipophilicity (LELP) scores above 3. The binding mechanism identified Tyr92 to be critical for binding, and this was corroborated via molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) calculations. The ligand A1 was predicted to possess antileishmanial properties with a probability of activity (Pa) of 0.362 and a probability of inactivity (Pi) of 0.066, while A5 and A6 possessed dermatological properties with Pa values of 0.205 and 0.249 and Pi values of 0.162 and 0.120, respectively. Structural similarity search via DrugBank identified vabicaserin, daledalin, zanapezil, imipramine, and cefradine with antileishmanial properties suggesting that the de-novo compounds could be explored as potential antileishmanial agents.

The potentials of Calotropis procera against filarial elephantiasis: an in-silico approach

Lymphatic filariasis is one of the major diseases that belong to the category of neglected tropical illness. Filarial nematodes are the cause of the disease and are transmitted to humans via blood-feeding arthropod vectors. Drugs such as Albendazole, Ivermectin and diethylcarbamazine are administered either individually or in combination to overcome the progress of the lymphatic filariasis. These drugs have some minor side effects like temporary hair loss, dizziness, nausea etc. The filarial parasites have multifunctional proteins including the Glutathione-s-transferase (GST) enzyme. This study aims at the identification of a natural molecule that has the potential to bind with the GST enzyme, which plays a major role in detoxification of endogenous electrophilic compounds. Thus the binding interrupts the detoxification process within the filarial parasite, Brugia malayi. A medicinal plant Calotropis procera, owing to its anthelmintic properties was searched for the presence of potential phytocompounds. The phytocompounds were docked against the homology modeled GST enzyme using the MOE software. The results were screened and analyzed based on the Lipinski rule of 5. N-octanoate was the phytocompound obtained based on molecular docking, subjected to molecular dynamics. These results require further in vitro and in vivo validation to consider n-octanoate as a potential drug candidate for lymphatic filariasis treatment.

Identification of the most damaging nsSNPs in the human CFL1 gene and their functional and structural impacts on cofilin-1 protein

The cofilin-1 protein, encoded by CFL1, is an actin-binding protein that regulates F-actin depolymerization and nucleation activity through phosphorylation and dephosphorylation. CFL1 has been implicated in the development of neurodegenerative diseases (Alzheimer's disease and Huntington's disease), neuronal migration disorders (lissencephaly, epilepsy, and schizophrenia), and neural tube closure defects. Mutations in CFL1 have been associated with impaired neural crest cell migration and neural tube closure defects. In our study, various computational approaches were utilized to explore single-nucleotide polymorphisms (SNPs) in CFL1. The Variation Viewer and gnomAD databases were used to retrieve CFL1 SNPs, including 46 nonsynonymous SNPs (nsSNPs). The functional and structural annotation of SNPs was performed using 12 sequence-based web applications, which identified 20 nsSNPs as being the most likely to be deleterious or disease-causing. The conservation of cofilin-1 protein structures was illustrated using the ConSurf and PROSITE web servers, which projected the 12 most deleterious nsSNPs onto conserved domains, with the potential to disrupt the protein's functionality. These 12 nsSNPs were selected for protein structure construction, and the DynaMut/DUET servers predicted that the protein variants V7G, L84P, and L99A were the most likely to be damaging to the cofilin-1 protein structure or function. The evaluation of molecular docking studies demonstrated that the L99A and L84P cofilin-1 variants reduce the binding affinity for actin compared with the native cofilin-1 structure, and molecular dynamic simulation studies confirmed that these variants might destabilize the protein structure. The consequences of putative mutations on protein-protein interactions and post-translational modification sites in the cofilin-1 protein structure were analyzed. This study represents the first complete approach to understanding the effects of nsSNPs within the actin-depolymerizing factor/cofilin family, which suggested that SNPs resulting in L84P (rs199716082) and L99A (rs267603119) variants represent significant CFL1 mutations associated with disease development.

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.

Function of SYDE C2-RhoGAP family as signaling hubs for neuronal development deduced by computational analysis

Recent investigations of neurological developmental disorders have revealed the Rho-family modulators such as Syde and its interactors as the candidate genes. Although the mammalian Syde proteins are reported to possess GTPase-accelerating activity for RhoA-family proteins, diverse species-specific substrate selectivities and binding partners have been described, presumably based on their evolutionary variance in the molecular organization. A comprehensive in silico analysis of Syde family proteins was performed to elucidate their molecular functions and neurodevelopmental networks. Predicted structural modeling of the RhoGAP domain may account for the molecular constraints to substrate specificity among Rho-family proteins. Deducing conserved binding motifs can extend the Syde interaction network and highlight diverse but Syde isoform-specific signaling pathways in neuronal homeostasis, differentiation, and synaptic plasticity from novel aspects of post-translational modification and proteolysis.

Electroactive reduced graphene oxide for highly sensitive detection of secretory non-structural 1 protein: A potential diagnostic biomarker for Japanese encephalitis virus

Fluorine Doped Tin Oxide (FTO) electrode was fabricated with reduced Graphene Oxide (rGO) for sensitive detection of Japanese encephalitis virus (JEV) non-structural 1 (NS1) protein. Beforehand, in-silico 3D structure, stability, and docking of recombinant JEV NS1 antigen (NS1-Ag) and antibody (Ab) was evaluated. The recombinant NS1 Ag of 42 kDa was produced in-house by successful cloning into pET-28a(+) plasmid and further expressed using BL21 Escherichia coli (E. coli) cells. The NS1 Ag was used to raise polyclonal antibodies (Ab) and both were characterized via Sodium Dodecyl Sulphate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Western Blot, Matrix-Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF), and Enzyme-Linked Immunosorbent Assay (ELISA). Further characterisation of all binding events such as rGO synthesis, and its conjugation with NS1 Ab, and NS1 Ag were confirmed through Fourier-Transform Infrared Spectroscopy (FTIR), Raman Spectroscopy, Energy Dispersive X-Ray Analysis (EDX), Scanning Electron Microscopy (SEM), Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV). The fabricated FTO electrode was optimised for various parameters such as pH, response time, temperature, concentration, and scan rate. The detection of JEV NS1 Ag was performed in buffer (LOD- 0.92 fM) as well in spiked serum (LOD- 1.3 fM) samples. The JEV NS1 Ab showed negligible cross-reactivity with other flaviviral NS1 Ag, provided a rapid response within 5 s, and remained stable up to 4 weeks. Furthermore, the fabricated immunosensor may be a potential candidate for further miniaturisation for accurate and early diagnosis of JEV in clinical samples.

Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods

A novel infectious agent, SARS-CoV-2, is responsible for causing the severe respiratory disease COVID-19 and death in humans. Spike glycoprotein plays a key role in viral particles entering host cells, mediating receptor recognition and membrane fusion, and are considered useful targets for antiviral vaccine candidates. Therefore, computational techniques can be used to design a safe, antigenic, immunogenic, and stable vaccine against this pathogen. Drawing upon the structure of the S glycoprotein, we are trying to develop a potent multi-epitope subunit vaccine against SARS-CoV-2. The vaccine was designed based on cytotoxic T-lymphocyte and helper T-lymphocyte epitopes with an N-terminal adjuvant via conducting immune filters and an extensive immunoinformatic investigation. The safety and immunogenicity of the designed vaccine were further evaluated via using various physicochemical, allergenic, and antigenic characteristics. Vaccine-target (toll-like receptors: TLR2 and TLR4) interactions, binding affinities, and dynamical stabilities were inspected through molecular docking and molecular dynamic (MD) simulation methods. Moreover, MD simulations for dimeric TLRs/vaccine in the membrane-aqueous environment were performed to understand the differential domain organization of TLRs/vaccine. Further, dynamical behaviors of vaccine/TLR systems were inspected via identifying the key residues (named HUB nodes) that control interaction stability and provide a clear molecular mechanism. The obtained results from molecular docking and MD simulation revealed a strong and stable interaction between vaccine and TLRs. The vaccine's ability to stimulate the immune response was assessed by using computational immune simulation. This predicted a significant level of cytotoxic T cell and helper T cell activation, as well as IgG, interleukin 2, and interferon-gamma production. This study shows that the designed vaccine is structurally and dynamically stable and can trigger an effective immune response against viral infections.

Computational Design of a Multi-epitope Vaccine Against Clostridium chauvoei: An Immunoinformatics Approach

Blackleg is an infectious disease of animals that is commonly caused by Clostridium chauvoei and characterized by localized muscle necrosis. In this study, proteome-mining and immunoinformatics approaches were applied to identify novel antigenic proteins and to construct a multi-epitope vaccine against C. chauvoei. All proteins of C. chauvoei strains were retrieved from the NCBI Microbial Genome Database containing both genomic and proteomic data of prokaryotes. The proteins were analyzed to exclude non-redundant sequences and to determine antigenic, virulent, and non-allergenic vaccine candidates through several online tools, resulting in seven protein candidates. Cytotoxic T and B cell epitopes of these proteins were evaluated through the tools present in the immune epitope database and the prioritized antigenic epitopes were then conjugated via appropriate linkers to construct the vaccine candidate. After the evaluation of physicochemical properties of the construct, the tertiary structure was modeled and refined through trRosetta and GalaxyRefine, respectively. The quality of the 3D structure was validated by ERRAT score, z-score, and Ramachandran plot and the construct was then docked with bovine Toll-like receptor 4 (TLR 4) using ClusPro. The docked complex was subjected to Molecular Mechanics/Generalized Born Surface Area in the HawkDock server and normal mode analysis in the iMODS simulation suite to assess the binding energy and stability of the complex, respectively. Overall, the vaccine construct was found stable and energetically feasible for bovine TLR 4 binding. Therefore, it can be used as a multi-epitope vaccine construct in clostridial vaccines to control the blackleg disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10989-021-10279-9.

Analysing the essential proteins set of Plasmodium falciparum PF3D7 for novel drug targets identification against malaria

BACKGROUND

Plasmodium falciparum is an obligate intracellular parasite of humans that causes malaria. Falciparum malaria is a major public health threat to human life responsible for high mortality. Currently, the risk of multi-drug resistance of P. falciparum is rapidly increasing. There is a need to address new anti-malarial therapeutics strategies to combat the drug-resistance threat.

METHODS

The P. falciparum essential proteins were retrieved from the recently published studies. These proteins were initially scanned against human host and its gut microbiome proteome sets by comparative proteomics analyses. The human host non-homologs essential proteins of P. falciparum were additionally analysed for druggability potential via in silico methods to possibly identify novel therapeutic targets. Finally, the PfAp4AH target was prioritized for pharmacophore modelling based virtual screening and molecular docking analyses to identify potent inhibitors from drug-like compounds databases.

RESULTS

The analyses identified six P. falciparum essential and human host non-homolog proteins that follow the key druggability features. These druggable targets have not been catalogued so far in the Drugbank repository. These prioritized proteins seem novel and promising drug targets against P. falciparum due to their key protein-protein interactions features in pathogen-specific biological pathways and to hold appropriate drug-like molecule binding pockets. The pharmacophore features based virtual screening of Pharmit resource predicted a lead compound i.e. MolPort-045-917-542 as a promising inhibitor of PfAp4AH among prioritized targets.

CONCLUSION

The prioritized protein targets may worthy to test in malarial drug discovery programme to overcome the anti-malarial resistance issues. The in-vitro and in-vivo studies might be promising for additional validation of these prioritized lists of drug targets against malaria.

Designing a multi-epitope vaccine candidate to combat MERS-CoV by employing an immunoinformatics approach

Currently, no approved vaccine is available against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes severe respiratory disease. The spike glycoprotein is typically considered a suitable target for MERS-CoV vaccine candidates. A computational strategy can be used to design an antigenic vaccine against a pathogen. Therefore, we used immunoinformatics and computational approaches to design a multi-epitope vaccine that targets the spike glycoprotein of MERS-CoV. After using numerous immunoinformatics tools and applying several immune filters, a poly-epitope vaccine was constructed comprising cytotoxic T-cell lymphocyte (CTL)-, helper T-cell lymphocyte (HTL)-, and interferon-gamma (IFN-γ)-inducing epitopes. In addition, various physicochemical, allergenic, and antigenic profiles were evaluated to confirm the immunogenicity and safety of the vaccine. Molecular interactions, binding affinities, and the thermodynamic stability of the vaccine were examined through molecular docking and dynamic simulation approaches, during which we identified a stable and strong interaction with Toll-like receptors (TLRs). In silico immune simulations were performed to assess the immune-response triggering capabilities of the vaccine. This computational analysis suggested that the proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat viral infections; however, experimental evaluations remain necessary to verify the exact safety and immunogenicity profile of this vaccine.

In silico designing of vaccine candidate against Clostridium difficile

Clostridium difficile is a spore-forming gram-positive bacterium, recognized as the primary cause of antibiotic-associated nosocomial diarrhoea. Clostridium difficile infection (CDI) has emerged as a major health-associated infection with increased incidence and hospitalization over the years with high mortality rates. Contamination and infection occur after ingestion of vegetative spores, which germinate in the gastro-intestinal tract. The surface layer protein and flagellar proteins are responsible for the bacterial colonization while the spore coat protein, is associated with spore colonization. Both these factors are the main concern of the recurrence of CDI in hospitalized patients. In this study, the CotE, SlpA and FliC proteins are chosen to form a multivalent, multi-epitopic, chimeric vaccine candidate using the immunoinformatics approach. The overall reliability of the candidate vaccine was validated in silico and the molecular dynamics simulation verified the stability of the vaccine designed. Docking studies showed stable vaccine interactions with Toll‐Like Receptors of innate immune cells and MHC receptors. In silico codon optimization of the vaccine and its insertion in the cloning vector indicates a competent expression of the modelled vaccine in E. coli expression system. An in silico immune simulation system evaluated the effectiveness of the candidate vaccine to trigger a protective immune response.

Integrated Core Proteomics, Subtractive Proteomics, and Immunoinformatics Investigation to Unveil a Potential Multi-Epitope Vaccine against Schistosomiasis

Schistosomiasis is a parasitic infection that causes considerable morbidity and mortality in the world. Infections of parasitic blood flukes, known as schistosomes, cause the disease. No vaccine is available yet and thus there is a need to design an effective vaccine against schistosomiasis. Schistosoma japonicum, Schistosoma mansoni, and Schistosoma haematobium are the main pathogenic species that infect humans. In this research, core proteomics was combined with a subtractive proteomics pipeline to identify suitable antigenic proteins for the construction of a multi-epitope vaccine (MEV) against human-infecting Schistosoma species. The pipeline revealed two antigenic proteins-calcium binding and mycosubtilin synthase subunit C-as promising vaccine targets. T and B cell epitopes from the targeted proteins were predicted using multiple bioinformatics and immunoinformatics databases. Seven cytotoxic T cell lymphocytes (CTL), three helper T cell lymphocytes (HTL), and four linear B cell lymphocytes (LBL) epitopes were fused with a suitable adjuvant and linkers to design a 217 amino-acid-long MEV. The vaccine was coupled with a TLR-4 agonist (RS-09; Sequence: APPHALS) adjuvant to enhance the immune responses. The designed MEV was stable, highly antigenic, and non-allergenic to human use. Molecular docking, molecular dynamics (MD) simulations, and molecular mechanics/generalized Born surface area (MMGBSA) analysis were performed to study the binding affinity and molecular interactions of the MEV with human immune receptors (TLR2 and TLR4) and MHC molecules (MHC I and MHC II). The MEV expression capability was tested in an Escherichia coli (strain-K12) plasmid vector pET-28a(+). Findings of these computer assays proved the MEV as highly promising in establishing protective immunity against the pathogens; nevertheless, additional validation by in vivo and in vitro experiments is required to discuss its real immune-protective efficacy.

Insilico drug repurposing using FDA approved drugs against Membrane protein of SARS-CoV-2

The novel coronavirus (SARS-CoV-2) outbreak has started taking away the millions of lives worldwide. Identification of known and approved drugs against novel coronavirus disease (COVID-19) seems to be an urgent need for the repurposing of the existing drugs. So, here we examined a safe strategy of using approved drugs of SuperDRUG2 database against modeled membrane protein (M-protein) of SARS-CoV-2 which is essential for virus assembly by using molecular docking-based virtual screening. A total of 3639 drugs from SuperDRUG2 database and additionally 14 potential drugs reported against COVID-19 proteins were selected. Molecular docking analyses revealed that nine drugs can bind the active site of M-protein with desirable molecular interactions. We therefore applied molecular dynamics simulations and binding free energy calculation using MM-PBSA to analyze the stability of the compounds. The complexes of M-protein with the selected drugs were simulated for 50 ns and ranked according to their binding free energies. The binding mode of the drugs with M-protein was analyzed and it was observed that Colchicine, Remdesivir, Bafilomycin A1 from COVID-19 suggested drugs and Temozolomide from SuperDRUG2 database displayed desirable molecular interactions and higher binding affinity towards M-protein. Interestingly, Colchicine was found as the top most binder among tested drugs against M-protein. We therefore additionally identified four Colchicine derivatives which can bind efficiently with M-protein and have better pharmacokinetic properties. We recommend that these drugs can be tested further through in vitro studies against SARS-CoV-2 M-protein.

Computational insights into the identification of a potent matrix metalloproteinase inhibitor from Indigofera aspalathoides to control cancer metastasis

Matrix metalloproteinases (MMPs) are the major proteolytic enzymes which assist in regulating the metastatic process by degrading the extracellular matrix proteins. In this study, we have investigated the anti-metastatic potential of major bioactive compounds in the medicinal plant Indigofera aspalathoides targeting matrix metalloproteinases (MMP2 & MMP9) and it's in silico pharmacokinetic profiles using computational studies. Indigofera aspalathoides (Sivanar vembu in Tamil) is a renowned medicinal herb in traditional Indian medicine which contains indigocarpan, mucronulatol, indigocarpan diacetate, erythroxydiol X and erythroxydiol Y as the major constituents. The 3-dimensional structure of MMP2 and MMP9 was designed by using I-tasser and Modeller and it was validated by PROCHECK. The structures of mucronulatol and indigocarpan have been retrieved from PubChem and indigocarpan diacetate, erythroxydiol X & Y were drawn by using Chemdraw Ultra 6.0. Batimastat was used as a positive control. Molecular docking was performed by using AutoDock 4.2 tools and AutoDock vina, an open-source program which signifies an effective interaction between the phytoligands and MMP2 & MMP9. From the results, AutoDock 4.2 have showed that indigocarpan possesses strong binding energy (ΔG) of - 7.68 kcal/mol towards MMP2 and - 6.35 kcal/mol towards MMP9, whereas batimastat showed binding energy (ΔG) of - 6.34 kcal/mol for MMP2 and - 5.66 kcal/mol for MMP9, meanwhile the results from AutoDock vina indicates that indigocarpan possesses strong binding energy (ΔG) of - 8.0 kcal/mol towards MMP2 and - 8.2 kcal/mol towards MMP9, whereas batimastat showed binding energy (ΔG) of - 7.2 kcal/mol for MMP2 and - 7.6 kcal/mol for MMP9. Also, the ADME and toxicity results suggest that the indigocarpan compound possesses a druggable pharmacokinetic potentiality and does not have carcinogenicity and Ames mutagenesis compared with other phytoligands. Hence, it is evident from our results that both AutoDock platforms strongly revealed that the phytoligand, indigocarpan possesses strong inhibitory activity against MMP2 and MMP9 to control cancer metastasis.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02731-w.

Computational exploration of vicine - an alkaloid glycoside mediated pathological hallmark of adenosine kinase to promote neurological disorder

Epilepsy disease is characterized by the neuronal dysfunction or abnormal neuronal activity of the brain which is regulated by astrocytes. These are glial cells and found to be the major regulators of the brain which are guided by the occurrence of adenosine kinase (ADK) enzyme in the central nervous system (CNS). During the normal physiological environment, ADK maintains the level of adenosine in the CNS. Dysfunction of ADK levels results in accumulation of adenosine levels in the CNS that leads to the pathophysiology of the brain such as astrogliosis which is a pathological hallmark of epileptic seizures. Vicine, an alkaloid glycoside in bitter gourd juice (Momordica charantia) is found to be toxic to the human system if the bitter gourd juice is consumed more. This compound inhibits ADK enzyme activity to lead epilepsy and seizure. Here, the toxic effect of vicine targeting ADK using computational predictions was investigated. The 3-dimensional structure of ADK has been constructed using I-Tasser, which has been refined by ModRefiner, GalaxyRefine, and 3D refine and it was endorsed using PROCHECK, ERRAT, and VADAR. 3D structure of the ligand molecule has been obtained from PubChem. Molecular docking has been achieved using AutoDock 4.2 software, from which the outcome showed the effective interaction between vicine and ADK, which attains binding free energy (∆G) of - 4.13 kcal/mol. Vicine molecule interacts with the active region ARG 149 of ADK and inhibits the functions of ADK that may cause imbalance in energy homeostasis. Also, pre-ADMET results robustly propose in which vicine possesses toxicity, and meanwhile, from the Ames test, it was shown as mutagenic. Hence, the results from our study suggest that vicine was shown to be toxic that suppresses the ADK activity to undergo pathological conditions in the neuronal junctions to lead epilepsy.

Identification of promiscuous T cell epitopes on Mayaro virus structural proteins using immunoinformatics, molecular modeling, and QM:MM approaches

The Mayaro virus (MAYV) belongs to genus Alphavirus (family Togaviridae) and has been reported in several countries, especially in tropical regions of America. Due to its outbreaks and potential lack of medication, an effective vaccine formulation is strongly required. This study aimed to predict promiscuous T cell epitopes from structural polyproteins of MAYV using an immunoinformatics approach. For this purpose, consensus sequences were used to identify short protein sequences capable of binding to MHC class I and class II alleles. Our analysis pointed out 4 MHC-I/TCD8+ and 21 MHC-II/TCD4+ epitopes on capside (1;3), E1 (2;5), E2 (1;10), E3 (0;2), and 6 K (0;1) proteins. These predicted epitopes were characterized by high antigenicity, immunogenicity, conservancy, non-allergenic, non-toxic, and good population coverage rate values for North and South American geographical areas. Afterwards, we used the crystal structure of human toll-like receptor 3 (TLR3) ectodomain as a template to predict, through docking essays, the placement of a vaccine prototype at the TLR3 receptor binding site. Finally, classical and quantum mechanics/molecular mechanics (QM:MM) computations were employed to improve the quality of docking calculations, with the QM part of the simulations being accomplished by using the density functional theory (DFT) formalism. These results provide important insights into the advancement of diagnostic platforms, the development of vaccines, and immunotherapeutic interventions.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Elucidation of the 3D structure of grape seed 7S globulin and its interaction with malvidin 3-glucoside: A molecular modeling approach

Plant proteins are biopolymers with interesting technological applications for the food industry due to their ability to interact with phenolic compounds such as anthocyanins. The 3D structure of the 7S globulin from grape seed was elucidated for the first time using a homology model. The constructed 3D model showed that grape seed 7S globulin is rich in α-helices and β-sheets stabilized by six disulfide bridges. The interaction with the major grape anthocyanin malvidin-3-glucoside was also assessed by Docking and Molecular Dynamic simulation. Theoretical results demonstrated that 7S globulin interacts with Mv3glc through hydrogen, alkyl and π-alkyl bonds and the flavylium cation is oriented towards a hydrophobic region of the protein, being protected from hydration. Results provide valuable insights for understanding the mechanisms involved in the molecular interaction of grape anthocyanins with grape seed proteins that could be relevant to use them as potential color protecting agents in food industry applications.

Discovery of a new non-substrate inhibitor of the 26.5 kDa glutathione transferase from Taenia solium by virtual screening

The inappropriate use of anthelmintics, such as praziquantel and albendazole, has generated resistance and the need to develop new drugs. Glutathione transferases, GSTs, are bisubstrate dimeric enzymes that constitute the main detoxification mechanism against electrophiles, drugs and oxidative damage in Taenia solium. Therefore, GSTs are important targets for the development of new anthelmintics. In this work, we reported a successful virtual screen aimed at the identification of novel inhibitors of a 26.5 kDa GST from T. solium (TsGST26). We found that a compound, i7, able to inhibit selectively TsGST26 concerning human GSTs, showing a non-competitive inhibition mechanism towards substrate glutathione with a K_i (GSH) of 55.7 μM and mixed inhibition towards the electrophilic substrate 1-chloro-2,4-dinitrobenzene with a K_i (CDNB) of 8.64 μM. These results are in agreement with those of docking simulations, which showed i7 binds a site adjacent to the electrophilic site and furthest from the glutathione site.

Computational investigation for modeling the protein-protein interaction of TasA(28-261)-TapA(33-253): a decisive process in biofilm formation by Bacillus subtilis

Biofilms have a significant role in microbial persistence, antibiotic resistance, and chronic infections; consequently, there is a pressing need for development of novel "anti-biofilm strategies." One of the fundamental mechanisms involved in biofilm formation is protein-protein interactions of "amyloid-like proteins" (ALPs) in the extracellular matrix. Such interactions could be potential targets for development of novel anti-biofilm strategies; therefore, assessing the structural features of these interactions could be of great scientific value. Characterization of structural features the of protein-protein interaction with conventional structure biology tools including X-ray diffraction and nuclear magnetic resonance is technically challenging, expensive, and time-consuming. In contrast, modeling such interactions is time-efficient and economical, and might provide deeper understanding of structural basis of interactions. Although it is often acknowledged that molecular modeling methods have varying accuracy, their careful implementation with supplementary verification methods can provide valuable insight and directions for future studies. With this reasoning, during the present study, the protein-protein interaction of TasA_(28-261)-TapA_(33-253) (which is a decisive process for biofilm formation by Bacillus subtilis) was modeled using in silico approaches, viz., molecular modeling, protein-protein docking, and molecular dynamics simulations. Results obtained here identified amino acid residues present within intrinsically disordered regions of both proteins to be critical for interaction. These results were further supported with principal component analyses (PCA) and free energy landscape (FEL) analyses. Results presented here represent novel finding, and we hypothesize that amino acid residues identified during the present study could be targeted for inhibition of biofilm formation by B. subtilis.

A candidate multi-epitope vaccine against SARS-CoV-2

In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2. The overall quality of the candidate vaccine was validated in silico and Molecular Dynamics Simulation confirmed the stability of the designed vaccine. Docking studies revealed stable interactions of the vaccine with Toll-Like Receptors and MHC Receptors. The in silico cloning and codon optimization supported the proficient expression of the designed vaccine in E. coli expression system. The efficiency of the candidate vaccine to trigger an effective immune response was assessed by an in silico immune simulation. The computational analyses suggest that the designed multi-epitope vaccine is structurally stable which can induce specific immune responses and thus, can be a potential vaccine candidate against SARS-CoV-2.

In silico study of the association of the HLA-A*31:01 allele (human leucocyte antigen allele 31:01) with neuroantigenic epitopes of PLP (proteolipid protein), MBP (myelin basic protein) and MOG proteins (myelin oligodendrocyte glycoprotein) for studying the multiple sclerosis disease pathogenesis

The main pathologic hallmark of multiple sclerosis is a demyelinating plaque that contains a prominent immunologic response dominated by T cells of the immune system. PLP (proteolipid protein), MPB (myelin basic protein), and Myelin oligodendrocyte glycoprotein (MOG) proteins are important autoantigens for the demyelinating of CNS in multiple sclerosis. There is good evidence indicating that T CD8⁺ cells and MHC class I molecules play an important role in this disease. The HLA-A*31:01 allele of MHC class I is a member of HLA-A3 superfamily and there is no clear report concerning the relationship of this allele with MS. Feeling this gap, we studied the possible association of the HLA-A*31:01 with MS by prediction of neuroantigenic epitopes of human MBP, PLP, and MOG proteins of myelin sheath using in silico methods. PLP did not show any neuroantigenic epitope, but the two epitopes of MBP and seven epitopes of MOG for HLA-A*31:01 were determined via bioinformatics servers. In silico study of the nine epitope showed that MOG195-204 (LIICYNWLHR) peptide of the membrane-associated/cytoplasmic part of human MOG has suitable binding affinity to the HLA-A*31:01 allele as a potential neuroantigenic epitope. Further investigations of this peptide revealed that the binding of C-terminal residue of this peptide has a more significant effect on binding to this allele than the N-terminal part of the peptide. Altogether, this combination of "LIICYNWLHR/A*31:01 allele "may play an important role in MS pathogenesis and this complex is suggested for further studies such as T cell receptor.Communicated by Ramaswamy H. Sarma.

A system-level approach to investigate alloxan-induced toxicity in microtubule-binding protein to lead type 2 diabetes mellitus

Microtubule-associated protein tau (MAPT) is a key protein, which is mainly identified as an essential factor for microtubule dynamics and neuronal outgrowth. Though tau has several functions, regulation of insulin signaling is one among them to control type 2 diabetes. Abnormal expression of tau protein leads to hyperphosphorylation and is known as tauopathies. The presence of alloxan occurs in refined wheat flour, especially in various baking products such as parotta, a well-known South Indian dish. In this study, the reduced form of alloxan called dialuric acid can enter the beta cells of islets of Langerhans and binds MAPT to induce toxicity by hyperphosphorylating the tau protein, which ultimately causes destruction to pancreatic beta cells, and it leads to diabetes mellitus. Here, the toxic effects of dialuric acid targeting MAPT through in silico computational predictions have been investigated. The 3D structure of MAPT protein was constructed through I-Tasser, and it has been refined and validated by GalaxyRefine and PROCHECK. The structure of ligand was retrieved from PubChem. Molecular docking was accomplished by AutoDock 4.2 software, and the results indicate the strong binding affinity between dialuric acid and MAPT protein, and it showed a binding free energy (∆G) of - 3.72 kcal/mol. Dialuric acid binds with the active region SER 232 of MAPT whereby it hyperphosphorylates the protein to become toxic. Also, ADMET results strongly suggest that the compound dialuric acid possesses toxic property, and similarly, Ames test confirmed that it was found to be mutagenic. Thus, our results strongly revealed that dialuric acid was found to be toxic which could be able to damage the beta cells of the pancreas and abates insulin signaling, and finally, it leads to DM.

In silico Investigations of the Mode of Action of Novel Colchicine Derivatives Targeting β-Tubulin Isotypes: A Search for a Selective and Specific β-III Tubulin Ligand

The cardinal role of microtubules in cell mitosis makes them interesting drug targets for many pharmacological treatments, including those against cancer. Moreover, different expression patterns between cell types for several tubulin isotypes represent a great opportunity to improve the selectivity and specificity of the employed drugs and to design novel compounds with higher activity only on cells of interest. In this context, tubulin isotype βIII represents an excellent target for anti-tumoral therapies since it is overexpressed in most cancer cells and correlated with drug resistance. Colchicine is a well-known antimitotic agent, which is able to bind the tubulin dimer and to halt the mitotic process. However, it shows high toxicity also on normal cells and it is not specific for isotype βIII. In this context, the search for colchicine derivatives is a matter of great importance in cancer research. In this study, homology modeling techniques, molecular docking, and molecular dynamics simulations have been employed to characterize the interaction between 55 new promising colchicine derivatives and tubulin isotype βIII. These compounds were screened and ranked based on their binding affinity and conformational stability in the colchicine binding site of tubulin βIII. Results from this study point the attention on an amide of 4-chlorine thiocolchicine. This colchicine-derivative is characterized by a unique mode of interaction with tubulin, compared to all other compounds considered, which is primarily characterized by the involvement of the α-T5 loop, a key player in the colchicine binding site. Information provided by the present study may be particularly important in the rational design of colchicine-derivatives targeting drug resistant cancer phenotypes.

Antibiotic resistance and inhibition mechanism of novel aminoglycoside phosphotransferase APH(5) from B. subtilis subsp. subtilis strain RK

Bacterial resistance towards aminoglycoside antibiotics mainly occurs because of aminoglycoside phosphotransferases (APHs). It is thus necessary to provide a rationale for focusing inhibitor development against APHs. The nucleotide triphosphate (NTP) binding site of eukaryotic protein kinases (ePKs) is structurally conserved with APHs. However, ePK inhibitors cannot be used against APHs due to cross reactivity. Thus, understanding bacterial resistance at the atomic level could be useful to design new inhibitors against such resistant pathogens. Hence, we carried out in vitro studies of APH from newly deposited multidrug-resistant organism Bacillus subtilis subsp. subtilis strain RK. Enzymatic modification studies of different aminoglycoside antibiotics along with purification and characterization revealed a novel class of APH, i.e., APH(5), with molecular weight 27 kDa approximately. Biochemical analysis of virtually screened inhibitor ZINC71575479 by coupled spectrophotometric assay showed complete enzymatic inhibition of purified APH(5). In silico toxicity study comparison of ZINC71575479 with known inhibitor of APH, i.e., tyrphostin AG1478, predicted its acceptable values for 96 h fathead minnow LC₅₀, 48 h Tetrahymena pyriformis IGC₅₀, oral rat LD₅₀, and developmental toxicity using different QSAR methodologies. Thus, the present study gives novel insight into the aminoglycoside resistance and inhibition mechanism of APH(5) by applying experimental and computational techniques synergistically.

Discovery of Potential Anti-infective Therapy Targeting Glutamine Synthetase in Staphylococcus xylosus

Glutamine synthetase (GS), which catalyzes the production of glutamine, plays essential roles in most biological growth and biofilm formation, suggesting that GS may be used as a promising target for antibacterial therapy. We asked whether a GS inhibitor could be found as an anti-infective agent of Staphylococcus xylosus (S. xylosus). Here, computational prediction followed by experimental testing was used to characterize GS. Sorafenib was finally determined through computational prediction. In vitro experiments showed that sorafenib has an inhibitory effect on the growth of S. xylosus by competitively occupying the active site of GS, and the minimum inhibitory concentration was 4 mg/L. In vivo experiments also proved that treatment with sorafenib significantly reduced the levels of TNF-α and IL-6 in breast tissue from mice mastitis, which was further confirmed by histopathology examination. These findings indicated that sorafenib could be utilized as an anti-infective agent for the treatment of infections caused by S. xylosus.

Role of Structural Bioinformatics in Drug Discovery by Computational SNP Analysis: Analyzing Variation at the Protein Level

With the completion of the human genome project at the beginning of the 21st century, the biological sciences entered an unprecedented age of data generation, and made its first steps toward an era of personalized medicine. This abundance of sequence data has led to the proliferation of numerous sequence-based techniques for associating variation with disease, such as genome-wide association studies and candidate gene association studies. However, these statistical methods do not provide an understanding of the functional effects of variation. Structure-based drug discovery and design is increasingly incorporating structural bioinformatics techniques to model and analyze protein targets, perform large scale virtual screening to identify hit to lead compounds, and simulate molecular interactions. These techniques are fast, cost-effective, and complement existing experimental techniques such as high throughput sequencing. In this paper, we discuss the contributions of structural bioinformatics to drug discovery, focusing particularly on the analysis of nonsynonymous single nucleotide polymorphisms. We conclude by suggesting a protocol for future analyses of the structural effects of nonsynonymous single nucleotide polymorphisms on proteins and protein complexes.

Docking Screens for Novel Ligands Conferring New Biology

It is now plausible to dock libraries of 10 million molecules against targets over several days or weeks. When the molecules screened are commercially available, they may be rapidly tested to find new leads. Although docking retains important liabilities (it cannot calculate affinities accurately nor even reliably rank order high-scoring molecules), it can often can distinguish likely from unlikely ligands, often with hit rates above 10%. Here we summarize the improvements in libraries, target quality, and methods that have supported these advances, and the open access resources that make docking accessible. Recent docking screens for new ligands are sketched, as are the binding, crystallographic, and in vivo assays that support them. Like any technique, controls are crucial, and key experimental ones are reviewed. With such controls, docking campaigns can find ligands with new chemotypes, often revealing the new biology that may be docking's greatest impact over the next few years.

Structural insights on identification of potential lead compounds targeting WbpP in Vibrio vulnificus through structure-based approaches

WbpP encoding UDP-GlcNAC C4 epimerase is responsible for the activation of virulence factor in marine pathogen Vibrio vulnificus (V. vulnificus) and it is linked to many aquatic diseases, thus making it a potential therapeutic target. There are few reported compounds that include several natural products and synthetic compounds targeting Vibrio sp, but specific inhibitor targeting WbpP are unavailable. Here, we performed structure-based virtual screening using chemical libraries such as Binding, TOSLab and Maybridge to identify small molecule inhibitors of WbpP with better drug-like properties. Deficient structural information forced to model the structure and the stable protein structure was obtained through 30 ns of MD simulations. Druggability regions are focused for new lead compounds and our screening protocol provides fast docking of entire small molecule library with screening criteria of ADME/Lipinski filter/Docking followed by re-docking of top hits using a method that incorporates both ligand and protein flexibility. Docking conformations of lead molecules interface displays strong H-bond interactions with the key residues Gly101, Ser102, Val195, Tyr165, Arg298, Val209, Ser142, Arg233 and Gln200. Subsequently, the top-ranking compounds were prioritized using the molecular dynamics simulation-based conformation and stability studies. Our study suggests that the proposed compounds may aid as a starting point for the rational design of novel therapeutic agents.

Homology modeling and virtual screening of inhibitors against TEM- and SHV-type-resistant mutants: A multilayer filtering approach

TEM and SHV are class-A-type β-lactamases commonly found in Escherichia coli and Klebsiella pneumoniae. Previous studies reported S130G and K234R mutations in SHVs to be 41- and 10-fold more resistant toward clavulanic acid than SHV-1, respectively, whereas TEM S130G and R244S also showed the same level of resistance. These selected mutants confer higher level of resistance against clavulanic acid. They also show little susceptibility against other commercially available β-lactamase inhibitors. In this study, we have used docking-based virtual screening approach in order to screen potential inhibitors against some of the major resistant mutants of SHV and TEM types β-lactamase. Two different inhibitor-resistant mutants from SHV and TEM were selected. Moreover, we have retained the active site water molecules within each enzyme. Active site water molecules were placed within modeled structure of the mutant whose structure was unavailable with protein databank. The novelty of this work lies in the use of multilayer virtual screening approach for the prediction of best and accurate results. We are reporting five inhibitors on the basis of their efficacy against all the selected resistant mutants. These inhibitors were selected on the basis of their binding efficacies and pharmacophore features.